• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.222-228
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• 2019

An extreme value analysis (EVA) is essential to obtain a design value for highly nonlinear variables such as long-term environmental data for wind and waves, and slamming or sloshing impact pressures. According to the extreme value theory (EVT), the extreme value distribution is derived by multiplying the initial cumulative distribution functions for independent and identically distributed (IID) random variables. However, in the position mooring of DNVGL, the sampled global maxima of the mooring line tension are assumed to be IID stochastic variables without checking their independence. The ITTC Recommended Procedures and Guidelines for Sloshing Model Tests never deal with the independence of the sampling data. Hence, a design value estimated without the IID check would be under- or over-estimated because of considering observations far away from a Weibull or generalized Pareto distribution (GPD) as outliers. In this study, the IID sampling data are first checked in an EVA. With no IID random variables, an automatic resampling scheme is recommended using the block maxima approach for a generalized extreme value (GEV) distribution and peaks-over-threshold (POT) approach for a GPD. A partial autocorrelation function (PACF) is used to check the IID variables. In this study, only one 5 h sample of sloshing test results was used for a feasibility study of the resampling IID variables approach. Based on this study, the resampling IID variables may reduce the number of outliers, and the statistically more appropriate design value could be achieved with independent samples.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.19-26
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• 2014

In this paper, we propose a polychotomous regression model when independent variables include both categorical and numerical variables. For categorical independent variables, we use direct sums, and tensor product splines are used for continuous independent variables. We use BIC for varible selections criterior. We implemented the algorithm and apply the algorithm to real data. The use of direct sums and tensor products outperformed the usual multinomial logistic regression model.

• Journal of the Chungcheong Mathematical Society
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• v.27 no.2
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• pp.157-163
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• 2014

Let {$X_i$, $1{\leq}i{\leq}n$} be a sequence of i.i.d. sequence of positive random variables with common absolutely continuous cumulative distribution function F(x) and probability density function f(x) and $E(X^2)$ < ${\infty}$. The random variables X + Y and $\frac{(X-Y)^2}{(X+Y)^2}$ are independent if and only if X and Y have gamma distributions. In addition, the random variables $S_n$ and $\frac{\sum_{i=1}^{m}(X_i)^2}{(S_n)^2}$ with $S_n=\sum_{i=1}^{n}X_i$ are independent for $1{\leq}m$ < n if and only if $X_i$ has gamma distribution for $i=1,{\cdots},n$.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.255-262
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• 1998

In this paper, we study the saddlepoint approximations for the ratio of independent random variables. In Section 2, we derive the saddlepoint approximation to the probability density function. In Section 3, we represent a numerical example which shows that the errors are small even for small sample size.

• Bulletin of the Korean Mathematical Society
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• v.41 no.3
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• pp.559-571
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• 2004

The aim of the present paper is to establish some nonlinear integral inequalities in two independent variables which provide explicit bounds on unknown functions. The inequalities given here can be used as tools in the qualitative theory of certain partial differential equations.

• Kyungpook Mathematical Journal
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• v.54 no.4
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• pp.545-554
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• 2014

We provide a new Ostrowski-type inequality involving functions of two independent variables, as well as some related results.

• Journal of the Chungcheong Mathematical Society
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• v.20 no.4
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• pp.411-418
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• 2007

Let $X_1$, ${\cdots}$, $X_n$ be nondegenerate and positive independent identically distributed(i.i.d.) random variables with common absolutely continuous distribution function F(x) and $E(X^2)$ < ${\infty}$. The random variables $X_1+{\cdots}+X_n$ and $\frac{X_1+{\cdots}+X_m}{X_1+{\cdots}+X_n}$are independent for 1 $1{\leq}$ m < n if and only if $X_1$, ${\cdots}$, $X_n$ have gamma distribution.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.1
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• pp.39-46
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• 1993

In developing a multiple regression relationship, independent variables are frequently measured with error. For these situations the problem of estimating unknown parameters has been extensively discussed in the literature while little attention has been given to the prediction problem. In this paper a criterion is developed for assessing the severeness of measurement errors in each independent variable on the predicted values. Using the developed criterion we can present a guideline as to which measurement error should be controlled for a more accurate prediction. Proposed methods are illustrated with a standard data system in work measurement.

• Journal of the Korean Mathematical Society
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• v.53 no.6
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• pp.1275-1292
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• 2016

The Marcinkiewicz-Zygmund strong law of large numbers for conditionally independent and conditionally identically distributed random variables is an existing, but merely qualitative result. In this paper, for the more general cases where the conditional order of moment belongs to (0, ${\infty}$) instead of (0, 2), we derive results on convergence rates which are quantitative ones in the sense that they tell us how fast convergence is obtained. Furthermore, some conditional probability inequalities are of independent interest.

• Journal of Information Technology Applications and Management
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• v.18 no.2
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• pp.61-89
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• 2011

Blog is a new global phenomenon, but many research papers about organizational blog have not been shown. In this study the influencing factors of the organizational blog usage are empirically investigated, and several guidelines are suggested to IT professionals who involves the design and implementation of the organizational blog. The research model consists of seven independent variables, one dependent variable, and two moderating variables. The following variables are established as the independent variables; information, interface, service, communication, enjoy, performance expectation, and social influence. Two dimensions such as need and orientation are suggested for the moderating variables, and the actual usage is adopted as a dependent variable. As a result of multiple regression analysis using a stepwise method, the independent variables except for interface and communication affect the actual usage of organizational blogs. The moderating effects for need and orientation are partially supported. The implications of this study are as the followings; (1) The empirical factors affecting the usage of organizational blogs are empirically investigated, (2) The affecting factors vary according to the type of organizational blogs, and (3) Some guidelines are suggested for organizational blog's design.